plan-of-attack

Machine Learning, Computer Vision, Natural Language Processing

Introduction To Python

Introduction to ML operation scientific and visualization libraries - pandas, numpy, matplotlib, seaborn...

Data Preprocessing and Exploratory Analysis

• Train Test Split
• Categorical features
• Missing values
• Scaling Data

Regression Algorithms

• Linear Regression
• Ridge & Lasso regression
• Polynomial Functions
• Algo's used as both Regressors and Classifiers

Classification Algorithms

• K-Nearest Neighbors (KNN)
• Logistic Regression
• Decision Trees
• Support Vector Machine (SVM)
• Boosting Algos

Clustering Algorithms

• K-means
• Density based clustering

Dimensionality Reduction

• Principal Component Analysis (PCA)
• Linear Discriminant Analysis (LDA)

Ensemble Methods

• Random Forest
• Bagging
• Voting

Deep Learning

• Introduction to tensorflow,
• Artificial Neural Networks (ANN)
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• Autoencoders and GANs

Reinforcement Learning

• Approaches and use cases
• Deep Q Learning
• openAI

Optimization techniques

• Hyperparameter Tuning
• Cross-Validation
• Grid Search cross-validation for automatic selection of best parameters
• Regularization
• Seperate Validation dataset

Resources

Data sources

• kaggle
• UCI
• quandl
• unicef
• data.world
• airbnb
• nasa

Learning Material

• python basics
• stanford notes
• Pyimagesearch